It is often desirable, even necessary, to find a succinct or compressed representation for an input sequence of numbers, especially given an input of a very large quantity of numbers. One commonly encountered context for such a problem is with predictive cost functions, which often are presented as a very large array of numbers.
To the extent that there has been some exploration of using a simple combination of library functions for such succinct or compressed representations, an extra benefit arises when a decomposition into the simple library functions yields a suggestion of a candidate simplification of the set of formulas used to compute the predictive cost functions. However, major problems continue to be met when potentially hundreds of millions of such predictive cost functions need to be stored in a general data repository for a given practical use, such as in general analysis and in profitability forecasting.